{"title":"利用空间回归确定影响 2021 年西爪哇废物产生的因素","authors":"Anik Djuraidah, Akbar Rizki, Tony Alfan","doi":"10.31764/jtam.v8i2.19664","DOIUrl":null,"url":null,"abstract":"Responsible consumption and production is the 12th of the seventeen SDGs which is difficult for developing countries to achieve due to high waste production. Indonesia is the second largest producer of food waste in the world. Garbage is solid waste generated from community activities. Population density is an indicator to estimate the amount of waste generated in an area. The choice of West Java Province as the research area is based on the fact that this Province has the second highest population density in Indonesia. This study aimed to determine the predictors/factors that influence waste production in the districts/cities of West Java Province. The data used in this study are total waste as a response variable and GRDP (gross domestic product), total spending per capita, average length of schooling, literacy rate, number of MSMEs (micro, small, and medium enterprises), and several recreational and tourism places, the number of people's markets, and the number of restaurants as predictors. The methods used in this research are spatial autoregressive regression/SAR, spatial Lag-X/SLX, and spatial Durbin/SDM. The results of this study show that the SAR is the best model with the lowest BIC (74.442) and pseudo-R-squared (0.7934). Factors that significantly affect total waste production are literacy levels, the number of MSMEs, the number of traditional markets, and the number of recreational and tourist places. ","PeriodicalId":489521,"journal":{"name":"JTAM (Jurnal Teori dan Aplikasi Matematika)","volume":"18 13","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Identifying Factors Affecting Waste Generation in West Java in 2021 Using Spatial Regression\",\"authors\":\"Anik Djuraidah, Akbar Rizki, Tony Alfan\",\"doi\":\"10.31764/jtam.v8i2.19664\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Responsible consumption and production is the 12th of the seventeen SDGs which is difficult for developing countries to achieve due to high waste production. Indonesia is the second largest producer of food waste in the world. Garbage is solid waste generated from community activities. Population density is an indicator to estimate the amount of waste generated in an area. The choice of West Java Province as the research area is based on the fact that this Province has the second highest population density in Indonesia. This study aimed to determine the predictors/factors that influence waste production in the districts/cities of West Java Province. The data used in this study are total waste as a response variable and GRDP (gross domestic product), total spending per capita, average length of schooling, literacy rate, number of MSMEs (micro, small, and medium enterprises), and several recreational and tourism places, the number of people's markets, and the number of restaurants as predictors. The methods used in this research are spatial autoregressive regression/SAR, spatial Lag-X/SLX, and spatial Durbin/SDM. The results of this study show that the SAR is the best model with the lowest BIC (74.442) and pseudo-R-squared (0.7934). Factors that significantly affect total waste production are literacy levels, the number of MSMEs, the number of traditional markets, and the number of recreational and tourist places. \",\"PeriodicalId\":489521,\"journal\":{\"name\":\"JTAM (Jurnal Teori dan Aplikasi Matematika)\",\"volume\":\"18 13\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-04-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"JTAM (Jurnal Teori dan Aplikasi Matematika)\",\"FirstCategoryId\":\"0\",\"ListUrlMain\":\"https://doi.org/10.31764/jtam.v8i2.19664\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"JTAM (Jurnal Teori dan Aplikasi Matematika)","FirstCategoryId":"0","ListUrlMain":"https://doi.org/10.31764/jtam.v8i2.19664","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
负责任的消费和生产是十七项可持续发展目标中的第 12 项目标,由于废物产量高,发展中国家很难实现这一目标。印度尼西亚是世界上第二大食物垃圾生产国。垃圾是社区活动产生的固体废物。人口密度是估算一个地区垃圾产生量的指标。之所以选择西爪哇省作为研究地区,是因为该省是印尼人口密度第二高的省份。本研究旨在确定影响西爪哇省各县/市废物产生量的预测因素/因子。本研究使用的数据包括作为响应变量的垃圾总量,以及作为预测变量的国内生产总值(GRDP)、人均总支出、平均受教育年限、识字率、微型和中小型企业(MSME)数量、若干休闲和旅游场所、人民市场数量以及餐馆数量。本研究采用的方法有空间自回归/SAR、空间 Lag-X/SLX、空间 Durbin/SDM。研究结果表明,SAR 是 BIC(74.442)和伪 R 方(0.7934)最低的最佳模型。对废物总产量有重大影响的因素包括识字水平、中小微企业数量、传统市场数量以及休闲和旅游场所数量。
Identifying Factors Affecting Waste Generation in West Java in 2021 Using Spatial Regression
Responsible consumption and production is the 12th of the seventeen SDGs which is difficult for developing countries to achieve due to high waste production. Indonesia is the second largest producer of food waste in the world. Garbage is solid waste generated from community activities. Population density is an indicator to estimate the amount of waste generated in an area. The choice of West Java Province as the research area is based on the fact that this Province has the second highest population density in Indonesia. This study aimed to determine the predictors/factors that influence waste production in the districts/cities of West Java Province. The data used in this study are total waste as a response variable and GRDP (gross domestic product), total spending per capita, average length of schooling, literacy rate, number of MSMEs (micro, small, and medium enterprises), and several recreational and tourism places, the number of people's markets, and the number of restaurants as predictors. The methods used in this research are spatial autoregressive regression/SAR, spatial Lag-X/SLX, and spatial Durbin/SDM. The results of this study show that the SAR is the best model with the lowest BIC (74.442) and pseudo-R-squared (0.7934). Factors that significantly affect total waste production are literacy levels, the number of MSMEs, the number of traditional markets, and the number of recreational and tourist places.